Towards Context-Aware Data Management for Ambient Intelligence

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

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Abstract

Ambient Intelligence (AmI) is a vision of future Information Society, where people are surrounded by an electronic environment which is sensitive to their needs, personalized to their requirements, anticipatory of their behavior, and responsive to their presence. It emphasizes on greater user-friendliness, user-empowerment, and more effective service support, with an aim to make peoplersquos daily activities more convenient, thus improving the quality of human life. To make AmI real, effective data management support is indispensable. High-quality information must be available to any user, anytime, anywhere, and on any lightweight device. Beyond that, AmI also raises many new challenges related to context-awareness and natural user interaction, entailing us to re-think current database techniques. The aim of this paper is to address the impact of AmI, particularly its user-centric context-awareness requirement on data management strategies and solutions. We first provide a multidimensional view of database access context. Taking diverse contextual information into account, we then present five context-aware data management strategies, using the most fundamental database operation-context-aware query request as a case in point. We execute the proposed strategies via a two-layered infrastructure, consisting of public data manager(s) and a private data manager. Detailed steps of processing a context-aware query are also described in the paper.
Original languageUndefined
Title of host publicationProceedings of the 15th International Conference on Database and Expert Systems Applications (DEXA 2004)
EditorsF. Galindo, M. Takizawa, R. Traunmüller
Place of PublicationBerlin
PublisherSpringer
Pages422-431
Number of pages10
ISBN (Print)3-540-22936-1
DOIs
Publication statusPublished - Aug 2004
Event15th International Conference on Database and Expert Systems Applications 2004 - Zaragoza, Spain, Zaragoza, Spain
Duration: 30 Aug 20043 Sep 2004
Conference number: 15

Publication series

NameLecture Notes in Computer Science
PublisherSpringer-Verlag
Volume3180

Conference

Conference15th International Conference on Database and Expert Systems Applications 2004
Abbreviated titleDEXA 2004
CountrySpain
CityZaragoza
Period30/08/043/09/04
Other30 Aug.-3 Sept. 2004

Keywords

  • DB-CAQ: CONTEXT-AWARE QUERYING
  • EWI-7987
  • IR-49312
  • METIS-221525

Cite this

Feng, L., Apers, P. M. G., & Jonker, W. (2004). Towards Context-Aware Data Management for Ambient Intelligence. In F. Galindo, M. Takizawa, & R. Traunmüller (Eds.), Proceedings of the 15th International Conference on Database and Expert Systems Applications (DEXA 2004) (pp. 422-431). (Lecture Notes in Computer Science; Vol. 3180). Berlin: Springer. https://doi.org/10.1007/b99664, https://doi.org/10.1007/978-3-540-30075-5_41
Feng, L. ; Apers, Peter M.G. ; Jonker, Willem. / Towards Context-Aware Data Management for Ambient Intelligence. Proceedings of the 15th International Conference on Database and Expert Systems Applications (DEXA 2004). editor / F. Galindo ; M. Takizawa ; R. Traunmüller. Berlin : Springer, 2004. pp. 422-431 (Lecture Notes in Computer Science).
@inproceedings{683ee970e39e4eb9b623dbd7e9cf54b8,
title = "Towards Context-Aware Data Management for Ambient Intelligence",
abstract = "Ambient Intelligence (AmI) is a vision of future Information Society, where people are surrounded by an electronic environment which is sensitive to their needs, personalized to their requirements, anticipatory of their behavior, and responsive to their presence. It emphasizes on greater user-friendliness, user-empowerment, and more effective service support, with an aim to make peoplersquos daily activities more convenient, thus improving the quality of human life. To make AmI real, effective data management support is indispensable. High-quality information must be available to any user, anytime, anywhere, and on any lightweight device. Beyond that, AmI also raises many new challenges related to context-awareness and natural user interaction, entailing us to re-think current database techniques. The aim of this paper is to address the impact of AmI, particularly its user-centric context-awareness requirement on data management strategies and solutions. We first provide a multidimensional view of database access context. Taking diverse contextual information into account, we then present five context-aware data management strategies, using the most fundamental database operation-context-aware query request as a case in point. We execute the proposed strategies via a two-layered infrastructure, consisting of public data manager(s) and a private data manager. Detailed steps of processing a context-aware query are also described in the paper.",
keywords = "DB-CAQ: CONTEXT-AWARE QUERYING, EWI-7987, IR-49312, METIS-221525",
author = "L. Feng and Apers, {Peter M.G.} and Willem Jonker",
note = "Imported from DIES and EWI/DB PMS [db-utwente:inpr:0000003584]",
year = "2004",
month = "8",
doi = "10.1007/b99664",
language = "Undefined",
isbn = "3-540-22936-1",
series = "Lecture Notes in Computer Science",
publisher = "Springer",
pages = "422--431",
editor = "F. Galindo and M. Takizawa and R. Traunm{\"u}ller",
booktitle = "Proceedings of the 15th International Conference on Database and Expert Systems Applications (DEXA 2004)",

}

Feng, L, Apers, PMG & Jonker, W 2004, Towards Context-Aware Data Management for Ambient Intelligence. in F Galindo, M Takizawa & R Traunmüller (eds), Proceedings of the 15th International Conference on Database and Expert Systems Applications (DEXA 2004). Lecture Notes in Computer Science, vol. 3180, Springer, Berlin, pp. 422-431, 15th International Conference on Database and Expert Systems Applications 2004, Zaragoza, Spain, 30/08/04. https://doi.org/10.1007/b99664, https://doi.org/10.1007/978-3-540-30075-5_41

Towards Context-Aware Data Management for Ambient Intelligence. / Feng, L.; Apers, Peter M.G.; Jonker, Willem.

Proceedings of the 15th International Conference on Database and Expert Systems Applications (DEXA 2004). ed. / F. Galindo; M. Takizawa; R. Traunmüller. Berlin : Springer, 2004. p. 422-431 (Lecture Notes in Computer Science; Vol. 3180).

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

TY - GEN

T1 - Towards Context-Aware Data Management for Ambient Intelligence

AU - Feng, L.

AU - Apers, Peter M.G.

AU - Jonker, Willem

N1 - Imported from DIES and EWI/DB PMS [db-utwente:inpr:0000003584]

PY - 2004/8

Y1 - 2004/8

N2 - Ambient Intelligence (AmI) is a vision of future Information Society, where people are surrounded by an electronic environment which is sensitive to their needs, personalized to their requirements, anticipatory of their behavior, and responsive to their presence. It emphasizes on greater user-friendliness, user-empowerment, and more effective service support, with an aim to make peoplersquos daily activities more convenient, thus improving the quality of human life. To make AmI real, effective data management support is indispensable. High-quality information must be available to any user, anytime, anywhere, and on any lightweight device. Beyond that, AmI also raises many new challenges related to context-awareness and natural user interaction, entailing us to re-think current database techniques. The aim of this paper is to address the impact of AmI, particularly its user-centric context-awareness requirement on data management strategies and solutions. We first provide a multidimensional view of database access context. Taking diverse contextual information into account, we then present five context-aware data management strategies, using the most fundamental database operation-context-aware query request as a case in point. We execute the proposed strategies via a two-layered infrastructure, consisting of public data manager(s) and a private data manager. Detailed steps of processing a context-aware query are also described in the paper.

AB - Ambient Intelligence (AmI) is a vision of future Information Society, where people are surrounded by an electronic environment which is sensitive to their needs, personalized to their requirements, anticipatory of their behavior, and responsive to their presence. It emphasizes on greater user-friendliness, user-empowerment, and more effective service support, with an aim to make peoplersquos daily activities more convenient, thus improving the quality of human life. To make AmI real, effective data management support is indispensable. High-quality information must be available to any user, anytime, anywhere, and on any lightweight device. Beyond that, AmI also raises many new challenges related to context-awareness and natural user interaction, entailing us to re-think current database techniques. The aim of this paper is to address the impact of AmI, particularly its user-centric context-awareness requirement on data management strategies and solutions. We first provide a multidimensional view of database access context. Taking diverse contextual information into account, we then present five context-aware data management strategies, using the most fundamental database operation-context-aware query request as a case in point. We execute the proposed strategies via a two-layered infrastructure, consisting of public data manager(s) and a private data manager. Detailed steps of processing a context-aware query are also described in the paper.

KW - DB-CAQ: CONTEXT-AWARE QUERYING

KW - EWI-7987

KW - IR-49312

KW - METIS-221525

U2 - 10.1007/b99664

DO - 10.1007/b99664

M3 - Conference contribution

SN - 3-540-22936-1

T3 - Lecture Notes in Computer Science

SP - 422

EP - 431

BT - Proceedings of the 15th International Conference on Database and Expert Systems Applications (DEXA 2004)

A2 - Galindo, F.

A2 - Takizawa, M.

A2 - Traunmüller, R.

PB - Springer

CY - Berlin

ER -

Feng L, Apers PMG, Jonker W. Towards Context-Aware Data Management for Ambient Intelligence. In Galindo F, Takizawa M, Traunmüller R, editors, Proceedings of the 15th International Conference on Database and Expert Systems Applications (DEXA 2004). Berlin: Springer. 2004. p. 422-431. (Lecture Notes in Computer Science). https://doi.org/10.1007/b99664, https://doi.org/10.1007/978-3-540-30075-5_41